Whole genome variants across 57 pig breeds enable comprehensive identification of genetic signatures that underlie breed features

Background:A large number of pig breeds are distributed around the world,their features and characteristics vary among breeds,and they are valuable resources.Understanding the underlying genetic mechanisms that explain across-breed variation can help breeders develop improved pig breeds.Results:In this study,we performed GWAS using a standard mixed linear model with three types of genome variants(SNP,InDel,and CNV)that were identified from public,whole-genome,sequencing data sets.We used 469 pigs of 57 breeds,and we identified and analyzed approximately 19 million SNPs,1.8 million InDels,and 18,016 CNVs.We defined six biological phenotypes by the characteristics of breed features to identify the associated genome variants and candidate genes,which included coat color,ear shape,gradient zone,body weight,body length,and body height.A total of 37 candidate genes was identified,which included 27 that were reported previously(e.g.,PLAG1 for body weight),but the other 10 were newly detected candidate genes(e.g.,ADAMTS9 for coat color).Conclusion:Our study indicated that using GWAS across a modest number of breeds with high density genome variants provided efficient mapping of complex traits.

rMVP: A Memory-efficient, Visualization-enhanced, and Parallel-accelerated Tool for Genome-wide Association Study

Along with the develoipment of high-throughput sequencing technologies,both sample size and SNP number are increasing rapidly in genome-wide association studies(GWAS),and the associated computation is more challenging than ever.Here,we present a memory-efficient,visualization-enhanced,and parallel-accelerated R package called“r MVP”to address the need for improved GWAS computation.r MVP can 1)effectively process large GWAS data,2)rapidly evaluate population structure,3)efficiently estimate variance components by Efficient Mixed-Model Association e Xpedited(EMMAX),Factored Spectrally Transformed Linear Mixed Models(Fa ST-LMM),and Haseman-Elston(HE)regression algorithms,4)implement parallel-accelerated association tests of markers using general linear model(GLM),mixed linear model(MLM),and fixed and random model circulating probability unification(Farm CPU)methods,5)compute fast with a globally efficient design in the GWAS processes,and 6)generate various visualizations of GWASrelated information.Accelerated by block matrix multiplication strategy and multiple threads,the association test methods embedded in r MVP are significantly faster than PLINK,GEMMA,and Farm CPU_pkg.r MVP is freely available at https://github.com/xiaolei-lab/r MVP.

Transcriptomic basis of neutrophil ratio variation induced by poly I:C stimulation in porcine peripheral blood

Neutrophils are vital components of defense mechanisms against invading pathogens and are closely linked with the individual antiviral capacity of pigs and other mammals. Neutrophilia is a well-known clinical characteristic of viral and bacterial infections. Using Affymetrix porcine genome microarrays, we investigated the gene expression profiles associated with neutrophil variation in porcine peripheral blood before and after polyriboinosinic-polyribocytidylic acid stimulation. Transcriptomic analysis showed 796 differentially expressed genes(DEGs) in extreme response(ER) pigs and 192 DEGs in moderate response(MR) pigs. Most DEGs were related to immune responses, included MXD1, CXCR4,CREG1, My D88, CD14, TLR2, TLR4, IRF3 and IRF7.Gene ontology analysis indicated that the DEGs of both ER and MR pigs were involved in common biological processes, such as cell proliferation, growth regulation,immune response, inflammatory response and cell activation. The ER and MR groups also showed differences in DEGs involved in biological processes. DEGs involved in cell division and cell cycle were specifically found in the ER pigs, whereas DEGs involved in cell migration were specifically found in the MR pigs. The study provides a basic understanding of the molecular basis for the antiviral capacity of pigs and other mammals.